Varying rebuild task priorities

ABSTRACT

A method begins by determining whether at least one encoded data slice of a corresponding set of encoded data slices associated with a primary storage unit requires rebuilding and includes one or more excess encoded data slices of the set of encoded data slices stored in a secondary storage unit. The method continues by identifying the excess encoded data slices based on scan response messages from the secondary storage units. The method continues by assigning, for each data segment associated with at least one of an encoded data slice requiring rebuilding and an excess encoded data slice, a priority level in accordance with a prioritization scheme. The method continues by facilitating, for each data segment, rebuilding of the encoded data slices requiring rebuilding and deletion of excess encoded data slices requiring deletion in accordance with the assigned priority level of the data segment.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 62/211,975,entitled “STORING ENCODED DATA SLICES IN A DISPERSED STORAGE NETWORK,”filed Aug. 31, 2015, which is hereby incorporated herein by reference inits entirety and made part of the present U.S. Utility PatentApplication for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION

Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of varying rebuildtask priorities in accordance with the present invention; and

FIG. 9A is a logic diagram of an example method of varying rebuild taskpriorities in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSTN memory 22for a user device, a group of devices, or for public access andestablishes per vault dispersed storage (DS) error encoding parametersfor a vault. The managing unit 18 facilitates storage of DS errorencoding parameters for each vault by updating registry information ofthe DSN 10, where the registry information may be stored in the DSNmemory 22, a computing device 12-16, the managing unit 18, and/or theintegrity processing unit 20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generateper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSTN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of varying rebuild task prioritiesin another embodiment of a dispersed storage network (DSN) that includesprimary storage units 900, secondary storage units 902, network 24 ofFIG. 1, and the distributed storage and task (DST) integrity processingunit 20 of FIG. 1. The primary storage units 900 include one or morestorage units 1-x. The secondary storage units 902 include one or morestorage units 1-y. Each storage unit may be implemented utilizing theDST execution (EX) unit 36 of FIG. 1. The DSN functions to prioritizerepair of storage of data.

In the case of a system using affinity, and/or trimmed writes, a rebuildmodule includes several new responsibilities. In addition to rebuildinglost encoded data slices (slices), restoring full health to the systemmay include: deleting excess slices (e.g., in a trimmed writes system),and recovering proper affinity (ensuring that all slices are at theirprimary location and that no slices are on the secondary locations).While recovering affinity is required to ensure proper failure toleranceof site outages, and equalized utilization, improper affinity statesdoes not significantly imperil data. Therefore, the rebuild module mayprioritize recovering lost slices compared to the less important tasks:cleaning up extra slices (which are generally harmless when the systemis not full) and restoring affinity (which in the worst cases leads tounequal utilization and less efficient reads). A combined approach willbundle rebuild tasks, e.g. when rebuilding a slice for a source that isnot at proper affinity, the rebuild module can tackle both tasks at thesame time. Therefore, for slices that are unhealthy and lack affinity,those sources may receive the highest priority of all.

In an example of operation of the prioritizing of the repair of thestorage of data, for each data segment of a plurality of data segmentsstored as a plurality of sets of encoded data slices in one or more ofprimary storage units and secondary storage units of the DSN, DSTintegrity processing unit 20 determines (and records) whether at leastone encoded data slice of a corresponding set of encoded data slicesassociated with a primary storage unit requires rebuilding and/orincludes one or more access encoded data slices of the set of encodeddata slices stored in at least one secondary storage unit. Thedetermining includes one or more of issuing scan request rebuildmessages 904 to primary storage units and secondary storage units forthe plurality of data segments, receiving scan response rebuild messages906, identifying the one encoded data slice requiring rebuilding basedon the scan response messages from the primary storage units (e.g.,identify a missing encoded data slice based on a desired pattern ofstorage of encoded data slices in primary storage units), identify theaccess encoded data slice based on scan response messages from thesecondary storage units (e.g., identify the access encoded data slicebased on a desired pattern of storage of extra encoded data slices insecondary storage units).

For each data segment associated with at least one of an encoded dataslice requiring rebuilding and including an excess encoded data slice,the DST integrity processing unit 20 assigns a priority level inaccordance with a prioritization scheme. The prioritization schemeincludes a highest priority scheme associated with a slice to berebuilt, a replacement slice to be deleted where the replacement sliceis associated with the slice to be rebuilt, and an extra encoded dataslice to be deleted. For instance, a second segment includes slice 2-2for rebuilding for storage unit 2 of the primary storage units, anassociated replacement slice 2-2 to be deleted from storage unit 2 ofthe secondary storage units, and an excess slice 2-1 to be deleted fromthe storage unit 1 of the secondary storage units.

The prioritization scheme further includes a next highest priorityscheme associated with a slice to be rebuilt and a replacement slice tobe deleted where the replacement slice is associated with the slice tobe rebuilt. For instance, a first segment includes slice 1-2 forrebuilding for storage unit 2 of the primary storage units and anassociated replacement slice 1-2 to be deleted from storage unit 2 ofthe secondary storage units.

The prioritization scheme further includes a next lowest priority schemeassociated with a slice to be rebuilt. For instance, a third segmentincludes slice 3-2 for rebuilding for storage unit 2 of the primarystorage units. The prioritization scheme further includes a lowestpriority scheme associated with a replacement slice to be deleted. Forinstance, a fourth segment includes an associated replacement slice 4-yto be deleted from storage unit y of the secondary storage units.

Having assigned the priority levels for slices to be rebuilt and/orslices to be deleted, for each data segment, the DST integrityprocessing unit 20 facilitates rebuilding encoded data slices requiringrebuilding and/or facilitates deletion of excess encoded data slicesrequiring deletion in accordance with the assigned priority level of thedata segment. The facilitating includes performing the rebuilding and/ordeletion on data segments associated with a highest priority level firstfollowed by a next highest priority level etc. When rebuilding, the DSTintegrity processing unit 20 issues, via the network 24, read slicerequests rebuilding messages, receives read slice response rebuildingmessages, generates a rebuilt encoded data slice, issues a write slicerequest rebuilding message that includes the rebuilt encoded data sliceto the primary storage unit, and receives a write slice responseconfirming storage of the rebuilt encoded data slice. When deletingexcess encoded data slices, the DST integrity processing unit 20 issues,via the network 24, a delete slice request affinity message 908 to acorresponding secondary storage unit and receives a delete sliceresponse affinity message 908 confirming deletion of the encoded dataslice for deletion.

FIG. 9A is a flowchart illustrating an example of varying rebuild taskpriorities of storage of data. In step 910, for each data segment, of aplurality of data segments, stored as a plurality of sets of encodeddata slices in one or more of primary storage units and secondarystorage units of a DSN, the method begins or continues at a step where aprocessing module of a distributed storage and task (DST) processingunit determines whether at least one encoded data slice of acorresponding set of encoded data slices associated with a primarystorage unit requires rebuilding and/or includes one or more excessencoded data slices of the set of encoded data slices stored in thesecondary storage units. For example, the processing module issues scanrequest rebuilding messages to primary storage units and secondarystorage units for the plurality of data segments, receives scan responserebuilding messages, identifies the one encoded data slice requiringrebuilding based on the scan response messages from the primary storageunits (e.g., identify a missing encoded data slice based on a desiredpattern), and identifies the excess encoded data slices based on scanresponse messages from the secondary storage units (e.g., identify theexcess encoded data slice based on the desired pattern).

In step 912, for each data segment associated with at least one of anencoded data slice recording rebuilding and an excess encoded dataslice, the method continues at the step where the processing moduleassigns a priority level to the data segment in accordance with aprioritization scheme (e.g., highest party, next highest priority, etc.,to a lowest priority). For each data segment, the method continues atstep 914, where the processing module facilitates rebuilding of encodeddata slice requiring rebuilding and/or deletion of the excess encodeddata slice requiring deletion in accordance with the assigned prioritylevel of the data segment. The facilitating is performed on datasegments associated with a highest priority first followed by a nexthighest priority etc. When rebuilding, the processing module issues readslice request rebuilding messages, receives read slice responserebuilding messages, generates a rebuilt encoded data slice, issues awrite slice request rebuilding message that includes the rebuilt encodeddata slice to a primary storage unit, and receives a write sliceresponse confirming storage of the rebuilt encoded data slice. Whendeleting a slice, the processing module issues a delete slice requestaffinity message to a corresponding secondary storage unit and receivesa delete slice response affinity message confirming deletion of theencoded data slice.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: determining, for each data segment of aplurality of data segments stored as a plurality of sets of encoded dataslices in one or more of primary storage units and secondary storageunits of a DSN, whether at least one encoded data slice of acorresponding set of encoded data slices associated with a primarystorage unit requires rebuilding and includes one or more excess encodeddata slices of the plurality of sets of encoded data slices stored inthe secondary storage units; identifying the excess encoded data slicesbased on scan response messages from the secondary storage units;assigning, for each data segment associated with at least one of anencoded data slice requiring rebuilding and an excess encoded dataslice, a priority level in accordance with a prioritization scheme; andfacilitating, for each data segment, rebuilding of the at least oneencoded data slice requiring rebuilding and deletion of excess encodeddata slices requiring deletion in accordance with the assigned prioritylevel of the data segment.
 2. The method of claim 1, wherein thedetermining comprises: issuing a scan request to rebuild messages to atleast one of each of the primary storage units and secondary storageunits for the plurality of data segments, receive scan responserebuilding messages; and identifying the at least one of an encoded dataslice requiring rebuilding based on the scan response rebuildingmessages from the primary storage units.
 3. The method of claim 2,wherein the identifying the at least one of an encoded data slicerequiring rebuilding is based on identifying a missing encoded dataslice based on a desired pattern.
 4. The method of claim 1 furthercomprising identifying the excess encoded data slice based on a desiredpattern.
 5. The method of claim 1, wherein the prioritization schemecomprises: highest priority for at least one encoded data slice to berebuilt, one corresponding replacement encoded data slice to be deleted,and at least one excess encoded data slice to be deleted; next highestpriority for at least one encoded data slice to be rebuilt, onecorresponding replacement encoded data slice to be deleted; next lowestpriority for at least one encoded data slice to be rebuilt; and lowestpriority for only one or more encoded data slices to be deleted.
 6. Themethod of claim 1 further comprising performing the facilitation on datasegments associated with a highest priority first followed by a nexthighest priority.
 7. The method of claim 1, wherein the rebuildingcomprises: issuing read slice request rebuilding messages; receivingread slice response rebuilding messages; generating a rebuilt encodeddata slice; issuing a write slice request rebuilding message thatincludes the rebuilt encoded data slice to the primary storage unit;receiving a write slice response confirming storage of the rebuiltencoded data slice; and deleting excess encoded data slices.
 8. Themethod of claim 1, wherein the deletion comprises: issuing a deleteslice request affinity message to a corresponding one of the secondarystorage units; and receiving a delete slice response affinity messageconfirming deletion of the encoded data slice.
 9. A computing device ofa group of computing devices of a dispersed storage network (DSN), thecomputing device comprises: an interface; a local memory; and aprocessing module operably coupled to the interface and the localmemory, wherein the processing module functions to: determine, for eachdata segment of a plurality of data segments stored as a plurality ofsets of encoded data slices in one or more of primary storage units andsecondary storage units of a DSN, whether at least one encoded dataslice of a corresponding set of encoded data slices associated with aprimary storage unit requires rebuilding and includes one or more excessencoded data slices of the plurality of sets of encoded data slicesstored in the secondary storage units; identify the excess encoded dataslices based on scan response messages from the secondary storage units;assign, for each data segment associated with at least one of an encodeddata slice requiring rebuilding and an excess encoded data slice, apriority level in accordance with a prioritization scheme; andfacilitate, for each data segment, rebuilding of the at least oneencoded data slice requiring rebuilding and deletion of excess encodeddata slices requiring deletion in accordance with the assigned prioritylevel of the data segment.
 10. The computing device of claim 9, whereinthe processing module functions to determine comprises: issuing a scanrequest to rebuild messages to primary storage units and secondarystorage units for the plurality of data segments, receive scan responserebuilding messages; and identifying the at least one encoded data slicerequiring rebuilding based on the scan response rebuilding messages fromthe primary storage units.
 11. The computing device of claim 10, whereinthe identifying the one encoded data slice requiring rebuildingcomprises identifying a missing encoded data slice based on a desiredpattern.
 12. The computing device of claim 9 wherein identifying theexcess encoded data slice is based on a desired pattern.
 13. Thecomputing device of claim 9, wherein the prioritization schemecomprises: highest priority for at least one encoded data slice to berebuilt, one corresponding replacement encoded data slice to be deleted,and at least one excess encoded data slice to be deleted; next highestpriority for at least one encoded data slice to be rebuilt, onecorresponding replacement encoded data slice to be deleted; next lowestpriority for at least one encoded data slice to be rebuilt; and lowestpriority for only one or more encoded data slices to be deleted.
 14. Thecomputing device of claim 9, wherein the rebuilding is performed on datasegments associated with a highest priority first followed by a nexthighest priority.
 15. The computing device of claim 9, wherein therebuilding comprises: issuing read slice request rebuilding messages;receiving read slice response rebuilding messages; generating a rebuiltencoded data slice; issuing a write slice request rebuilding messagethat includes the rebuilt encoded data slice to a primary storage unit;receiving a write slice response confirming storage of the rebuiltencoded data slice; and deleting excess encoded data slices.
 16. Thecomputing device of claim 9, wherein the deletion of excess encoded dataslices comprises: issuing a delete slice request affinity message to acorresponding one of the secondary storage units; and receiving a deleteslice response affinity message confirming deletion of the encoded dataslice.
 17. A method for execution by one or more processing modules ofone or more computing devices of a dispersed storage network (DSN), themethod comprises: determining, for each data segment of a plurality ofdata segments stored as a plurality of sets of encoded data slices inone or more of primary storage units and secondary storage units of aDSN, whether at least one encoded data slice of a corresponding set ofencoded data slices associated with a primary storage unit requiresrebuilding and/or includes one or more excess encoded data slices of theplurality of sets of encoded data slices stored in the secondary storageunits; identifying the excess encoded data slices based on scan responsemessages from the secondary storage units; assigning, for each datasegment associated with at least one of an encoded data slice requiringrebuilding and an excess encoded data slice, a priority level inaccordance with a prioritization scheme; and facilitating, for each datasegment, rebuilding of the at least one encoded data slice requiringrebuilding and deletion of excess encoded data slices requiring deletionin accordance with the assigned priority level of the data segment.